Research Resource for Complex Physiologic Signals

复杂生理信号的研究资源

基本信息

批准号：
8373058
负责人：
Ary Louis Goldberger
金额：
$ 74.07万
依托单位：
BETH ISRAEL DEACONESS MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
2007
资助国家：
美国
起止时间：
2007-09-01 至 2015-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8373058
关键词：
Acute Address Aging Algorithms Antihypertensive Agents Archives Attention Basic Science Biological Markers Biological Models Biomedical Engineering Cardiology Cardiopulmonary Clinical Collaborations Collection Communities Complex Computer software Coupled Critical Care Data Data Collection Databases Diagnosis Disease Engineering Event Functional disorder Funding Goals Growth Health Industry Intensive Care Laboratories Lead Medical Students Methods Monitor Morphologic artifacts Noise Online Systems Patient Monitoring Patients Physiological Process Property Publications Research Research Personnel Resources Running Series Services Signal Transduction Site Sleep Sleep Apnea Syndromes Specialist Syndrome Testing Time United States National Institutes of Health Work base computerized data processing computerized tools data sharing graphical user interface improved innovation instrument interest meetings new technology novel open source programs prototype repository time interval tool trend virtual

项目摘要

DESCRIPTION (provided by applicant): PhysioNet, established in 1999 as the NIH-sponsored Research Resource for Complex Physiologic Signals, has attained a preeminent status among data and software resources in biomedicine. Its data archive, PhysioBank, was the first, and remains the world's largest, most comprehensive and most widely used repository of time-varying physiologic signals. Its software collection, PhysioToolkit, supports exploration and quantitative analyses of PhysioBank and similar data with a wide range of well-documented, rigorously tested, open-source software that can be run on any platform. PhysioNet's team of researchers leverages results of other funded projects to drive the creation and enrichment of: " Data collections that provide increasingly comprehensive, multifaceted views of pathophysiology over long time intervals, such as the MIMIC II (Multiparameter Monitoring in Intensive Care) Database of critical care patients; " Analytic methods that lead to more timely and accurate diagnoses (such as prediction of acute hypotensive events), and elucidation of dynamical changes associated with disease and aging (such as cardiopulmonary interactions during sleep disordered breathing syndrome); " User interfaces, reference materials and services that add value and improve accessibility to PhysioNet's data and software (such as PhysioNetWorks, a virtual laboratory for data sharing). Impact: PhysioNet is a proven enabler and accelerator of innovative research by specialists, young investigators and trainees alike, working on independent projects and focused biomedical engineering challenges made possible by data that are inaccessible otherwise. Through its PhysioNetWorks, the Resource gives researchers new tools and the opportunity not merely to meet NIH data sharing mandates, but to enrich the data commons with accessible, valuable contributions. By providing free access to its unique and wide- ranging data and software collections, PhysioNet enables studies that lead to an average of 70 scholarly publications per month (well over 5000 studies since its inception by academic, clinical, and industry-affiliated researchers worldwide. Specific aims: For the next 5 years we aim to: 1. Accelerate PhysioNet's growth with new technology and data; 2. Drive relevant innovation through a vigorous research program on complex physiologic signals; 3. Stimulate and challenge a growing community of investigators. PUBLIC HEALTH RELEVANCE: PhysioNet, the Research Resource for Complex Physiological Signals, maintains the world's largest, most comprehensive, and most widely used repository of time-varying physiological signals and associated signal-processing software, and makes them freely available to the research community. PhysioNet is a proven enabler and accelerator of innovative research by specialists and non- specialists alike, working on independent projects and focused engineering challenges made possible by data that are inaccessible otherwise.

描述（由申请人提供）：Physionet成立于1999年，是用于复杂生理信号的NIH赞助的研究资源，在生物医学的数据和软件资源之间已获得了杰出的状态。它的数据存档，物理库是第一个，并且仍然是世界上最大，最全面，最广泛使用的时间变化的生理信号存储库。它的软件收集PysiotoolKit，支持对物理库的探索和定量分析，以及类似数据，具有广泛记录的，严格测试的开源软件，可以在任何平台上运行。 Physionet的研究人员团队利用其他资助项目的结果来推动：“在长期间隔内提供越来越全面，多方面的病理生理学观点的数据收集，例如模拟II（诸如密集型护理中的多疗程表监测）（在密集型护理中监测）对重症监护患者的数据库进行了更及时的诊断，例如，及时诊断；阐明与疾病和衰老相关的动态变化（例如睡眠失调呼吸综合征期间的心肺相互作用）；用户界面，参考材料和服务增加价值并改善了对Physionet数据和软件的可访问性（例如Physionetworks，一个用于数据共享的虚拟实验室）。影响：Physionet是专业的和加速专家的创新研究者，专家研究人员，年轻的调查人员和受训者都在独立的生物学上进行的挑战，并通过其范围进行生物启发，以使其通过生物技术进行挑战，否则可以通过其范围进行挑战。为研究人员提供新的工具和机会，不仅可以满足NIH数据共享授权，还可以通过可访问的，有价值的贡献来丰富数据共享。 TO：1。通过新技术和数据加速生理学；公共卫生相关性：Physionet，复杂生理信号的研究资源，维持世界上最大，最全面，最广泛使用的时变生理信号和相关信号处理软件的存储库，并可以免费提供研究社区。 Physionet是专家和非专家的创新研究促成者和加速器，他们从事独立项目和专注的工程挑战，这是由于无法访问的数据所带来的。